Y. X. Rachel Wang

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Coauteurs

Haiyan Huang, ProfessorUniversity of California, BerkeleyAdresse e-mail validée de stat.berkeley.edu
peter bickelProfessor of Statistics, UC BerkeleyAdresse e-mail validée de stat.berkeley.edu
Purnamrita SarkarAssociate Professor, Statistics and Data Sciences, University of Texas at AustinAdresse e-mail validée de austin.utexas.edu
Wing Hung WongStanford UniversityAdresse e-mail validée de stanford.edu
Yingxin LinYale UniversityAdresse e-mail validée de yale.edu
Oana UrsuScientist, Cellular and Tissue Genomics, GenentechAdresse e-mail validée de gene.com
Anshul KundajeAssociate Professor, Dept. of Genetics, Dept. of Computer Science, Stanford UniversityAdresse e-mail validée de stanford.edu
Anand BhaskarWaymoAdresse e-mail validée de waymo.com
Soumendu Sundar MukherjeeAssistant Professor at Statistics and Mathematics Unit, Indian Statistical Institute, KolkataAdresse e-mail validée de isical.ac.in
Matthias SteinrueckenUniversity of Chicago, Department of Ecology & EvolutionAdresse e-mail validée de uchicago.edu
Xin TongAssociate Professor, Department of Data Sciences and Operations, University of Southern CaliforniaAdresse e-mail validée de marshall.usc.edu
Jingyi Jessica LiProfessor, Department of Statistics, University of California at Los Angeles (UCLA)Adresse e-mail validée de stat.ucla.edu
Bowei YanUniversity of Texas at AustinAdresse e-mail validée de utexas.edu
Qiying WangThe University of SydneyAdresse e-mail validée de maths.usyd.edu.au
Mingzhang YinUniversity of FloridaAdresse e-mail validée de ufl.edu
Ke LiuDepartment of Pediatrics and Human Development, Michigan State UniversityAdresse e-mail validée de msu.edu
Matteo SesiaUniversity of Southern CaliforniaAdresse e-mail validée de usc.edu

Suivre

Y. X. Rachel Wang

School of Mathematics and Statistics, University of Sydney

Adresse e-mail validée de sydney.edu.au

Statistical network modelling statistical machine learning computational biology


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Selective coating of holes in microstructured optical fiber and its application to in-fiber absorptive polarizers X Zhang, R Wang, FM Cox, BT Kuhlmey, MCJ Large Optics express 15 (24), 16270-16278, 2007	465	2007
Review on statistical methods for gene network reconstruction using expression data YXR Wang, H Huang Journal of theoretical biology 362, 53-61, 2014	212	2014
Likelihood-based model selection for stochastic block models YXR Wang, PJ Bickel The Annals of Statistics 45 (2), 500-528, 2017	201	2017
Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data A Bhaskar, YXR Wang, YS Song Genome research 25 (2), 268-279, 2015	95	2015
GenomeDISCO: A concordance score for chromosome conformation capture experiments using random walks on contact map graphs O Ursu, N Boley, M Taranova, YXR Wang, GG Yardimci, W Stafford Noble, ... Bioinformatics 34 (16), 2701-2707, 2018	94	2018
scJoint integrates atlas-scale single-cell RNA-seq and ATAC-seq data with transfer learning Y Lin, TY Wu, S Wan, JYH Yang, WH Wong, YX Wang Nature Biotechnology 40 (5), 703-710, 2022	79	2022
Inferring gene–gene interactions and functional modules using sparse canonical correlation analysis YXR Wang, K Jiang, LJ Feldman, PJ Bickel, H Huang The Annals of Applied Statistics 9 (1), 300-323, 2015	45	2015
An explicit transition density expansion for a multi-allelic Wright–Fisher diffusion with general diploid selection M Steinrücken, YXR Wang, YS Song Theoretical population biology 83, 1-14, 2013	39	2013
Gene coexpression measures in large heterogeneous samples using count statistics YXR Wang, MS Waterman, H Huang Proceedings of the National Academy of Sciences 111 (46), 16371-16376, 2014	36	2014
Mean field for the stochastic blockmodel: Optimization landscape and convergence issues SS Mukherjee, P Sarkar, RYX Wang, B Yan Advances in neural information processing systems, 2018	26	2018
Nonparametric cointegrating regression with NNH errors Q Wang, YXR Wang Econometric Theory 29 (1), 1-27, 2013	21	2013
On hyperparameter tuning in general clustering problemsm X Fan, Y Yue, P Sarkar, YXR Wang International Conference on Machine Learning, 2996-3007, 2020	18	2020
A theoretical case study of structured variational inference for community detection M Yin, YXR Wang, P Sarkar International Conference on Artificial Intelligence and Statistics, 3750-3761, 2020	17	2020
Network modeling in biology: statistical methods for gene and brain networks YXR Wang, L Li, JJ Li, H Huang Statistical Science 36 (1), 89-108, 2021	15	2021
Mini-Batch Metropolis–Hastings With Reversible SGLD Proposal TY Wu, YX Rachel Wang, WH Wong Journal of the American Statistical Association, 1-9, 2020	11*	2020
Generalized correlation measure using count statistics for gene expression data with ordered samples YXR Wang, K Liu, E Theusch, JI Rotter, MW Medina, MS Waterman, ... Bioinformatics 34 (4), 617-624, 2018	11	2018
When random initializations help: a study of variational inference for community detection P Sarkar, YXR Wang, SS Mukherjee Journal of Machine Learning Research 22 (22), 1-46, 2021	7	2021
Network modelling of topological domains using Hi-C data YXR Wang, P Sarkar, O Ursu, A Kundaje, PJ Bickel The annals of applied statistics 13 (3), 1511, 2019	6	2019
A Unified Framework for Tuning Hyperparameters in Clustering Problems X Fan, Y Yue, P Sarkar, YX Wang arXiv preprint arXiv:1910.08018, 2019	4	2019
Statistics in everyone’s backyard: An impact study via citation network analysis L Wang, X Tong, YXR Wang Patterns 3 (8), 2022	3	2022

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